## 基本散点图展示 ### 应用场景 箱型图应用非常常见，比如：两组比较，多组比较，多组里面的两两比较  ### 利用ggplot2创建boxplot ```R # rt为2.1 scatter plot所展示的数据 # rt_box如上图所示 rt <- read.table(file = "/Users/stead/Documents/SourceTree/gitbook/R_visualization/data/LUAD_test.txt", header = TRUE, row.names = 1, stringsAsFactors = FALSE) # 准备ggplot2所需数据格式 rt_box <- data.frame(cbind(as.numeric(rt['TP53',]), c(rep('tumor', 57), rep('normal', 57)))) colnames(rt_box) <- c('TP53', 'group') rt_box$TP53 <- as.numeric(rt_box$TP53) ``` ```R library(ggplot2) P <- ggplot(rt_box, aes(x = group, y = TP53)) + geom_boxplot(outlier.colour="red", outlier.shape=8, outlier.size=4) print(P) ```  ```R # P 来自于上图 P + geom_jitter(shape=16, position=position_jitter(0.2))#在boxplot中加入具体表达值所在的位置点 ```  ```R P2 <- ggplot(rt_box, aes(x = group, y = TP53, color = group)) + geom_boxplot() + theme_classic() #改变下主题 print(P2) ```  ```R P3 <- ggplot(rt_box, aes(x = group, y = TP53, fill = group)) + geom_boxplot() + theme_classic() + geom_dotplot(binaxis='y', stackdir='center', position=position_dodge(1)) print(P3) ```